Search

Exploring efficient transition-metal-based electrocatalysts for oxygen evolution reaction (OER) is imperative but remain challenging for sustainable energy storage and conversion systems. Foreign species doping is a significant regulation strategy to enhance the intrinsic activity of host matrix. However, the potential relationship of structure-activity caused by guest doping elements is seldom tracked systematically. In this case, both theoretical screening and experimental verification are complementarily employed to investigate the guest doping effects of ten first-row transition metals (Sc~Zn) on bimetallic NiCo layered double hydroxide (NiCo-LDH). As a result, the optimized Fe-doped NiCo-LDH is identified as the most promising candidate toward alkaline electrocatalytic OER, which exhibits the quasi-industrial current density of 1000 mA cm-2 at overpotential of400 mV. Meanwhile, it also shows impressively long-term stability of 500 h at 500 mA cm-2 with a negligible activity loss. Moreover, in situ electrochemical Raman spectroscopy unveils the dynamic structure evolution from pre-catalytic state (Fe-NiCo-LDH) to metal oxyhydroxide (Fe-(NiCo)OOH) during the oxidation reaction, and ab-initio molecular dynamics simulations are further performed to confirm the thermodynamic stability of activated Fe-(NiCo)OOH phase. This work provides a promising platform for exploring the critical role of transition metal guest doping on host matrix in developing industrially required OER electrocatalysts. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) classification, due to its characteristic combination of images and spectra, has important applications in various fields through pixel-level image classification. The fusion of spatial–spectral features is a topic of great interest in the context of hyperspectral image classification, which typically requires selecting a larger spatial neighborhood window, potentially leading to overlaps between training and testing samples. Vision Transformer (ViTs), with their powerful global modeling abilities, have had a significant impact in the field of computer vision through various variants. In this study, an ensemble learning framework for HSI classification is proposed by integrating multiple variants of ViTs, achieving high-precision pixel-level classification. Firstly, the spatial shuffle operation was introduced to preprocess the training samples for HSI classification. By randomly shuffling operations using smaller spatial neighborhood windows, a greater potential spatial distribution of pixels can be described. Then, the training samples were transformed from a 3D cube to a 2D image, and a learning framework was built by integrating seven ViT variants. Finally, a two-level ensemble strategy was employed to achieve pixel-level classification based on the results of multiple ViT variants. Our experimental results demonstrate that the proposed ensemble learning framework achieves stable and significantly high classification accuracy on multiple publicly available HSI datasets. The proposed method also shows notable classification performance with varying numbers of training samples. Moreover, herein, it is proven that the spatial shuffle operation plays a crucial role in improving classification accuracy. By introducing superior individual classifiers, the proposed ensemble framework is expected to achieve even better classification performance. [ABSTRACT FROM AUTHOR]

Developing a cost-effective and highly efficient electrocatalyst for the hydrogen economy remains a significant challenge due mainly to the high overpotentials of the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Herein, we propose an effective modification strategy by encapsulating a small amount of Ru nanoclusters (NCs) into g-C3N4 rich in N-vacancies (VN). Systematic experiments were carried out to investigate the formation process of Ru NCs and demonstrate the strong interaction between Ru NCs and substrates. The optimized Ru NCs/VN-C3N4 displays a unique porous structure along with plentiful defects, maximizing the exposure of the active sites. As expected, Ru NCs/VN-C3N4 presents a preferable electrocatalytic activity with an overpotential of 8 mV for the HER and 200 mV for the OER at a current density of 10 mA cm−2, along with an ultra-high mass activity of Ru. DFT calculations further substantiate the superior HER and OER performance of Ru NCs/VN-C3N4, and confirm that the introduction of abundant VN effectively modulates the d-band center, intermediate binding energies and structural stability. When integrated into a symmetric electrolyzer, the cell voltage remarkably reduces to 1.488 V with splendid stability in alkaline medium, outperforming nearly all commercial electrocatalysts. This work sheds light on a novel avenue for the rational design of new-generation bifunctional electrocatalysts to promote the popularization of the hydrogen economy. [ABSTRACT FROM AUTHOR]

Ultraviolet (UV) radiation is the primary exogenous inducer of skin pigmentation, although the mechanism has not been fully elucidated. N6‐methyladenosine (m6A) modification is one of the key epigenetic form of gene regulation that affects multiple biological processes. The aim of this study was to explore the role and underlying mechanisms of m6A modification in UVB‐induced melanogenesis. Low‐dose UVB increased global m6A modification in melanocytes (MCs) and MNT1 melanoma cell line. The GEPIA database predicted that methyltransferase METTL3 is positively correlated with the melanogenic transcription factor MITF in the sun‐exposed skin tissues. After METTL3 respectively overexpressed and knocked down in the MNT1, the melanin content and melanogenesis‐related genes were significantly upregulated after overexpression of METTL3, especially with UVB irradiation, and downregulated after METTL3 knockdown. METTL3 levels were also higher in melanocytic nevi with high melanin content. METTL3 overexpression and knockdown also altered the protein level of YAP1. SRAMP analysis predicted four high‐potential m6A modification sites on YAP1 mRNA, of which three were confirmed by methylated RNA immunoprecipitation. Inhibition of YAP1 expression can partially reverse melanogenesis induced by overexpression of METTL3. In conclusion, UVB irradiation promotes global m6A modification in MCs and upregulates METTL3, which increases the expression level of YAP1 through m6A modification, thereby activating the co‐transcription factor TEAD1 and promoting melanogenesis. [ABSTRACT FROM AUTHOR]

Fabrication of transparent AlON ceramics is extra sensitive to both particle size of starting powder and sintering additive due to shuttling transformation between AlON and Al2O3 + AlN during heating. One possible solution is to select robust additive to suppress the shuttling transformation. In this work, three AlON powders with different median particle sizes of 0.6, 0.9, and 1.1 μm were prepared. After studying the effect of CaCO3 on densification process, AlON ceramics with the maximum transmittance of ≥81.1% were successfully fast prepared by pressureless sintering (PS) at 1880°C for only 2.5 h by using three AlON powders doped with different CaCO3 amount. Specifically, AlON ceramics prepared from 1.1 μm with 0.5–0.8 wt.% CaCO3 doping consistently showed the maximum transmittance of ≥85.3%, which indicates that CaCO3 can serve as a robust additive to enable fast fabrication of highly transparent AlON ceramics even by PS. [ABSTRACT FROM AUTHOR]

Fiber fault detection is crucial for maintaining the quality of optical communication, especially in well-established optical access networks with extended distances and a growing number of subscribers. However, the increasing insertion loss in fiber links presents challenges for traditional fault-detection methods in capturing fault echoes. To overcome these limitations, we propose a modulation-enhanced external-cavity-resonant-frequency method that utilizes a laser for fault echo reception, providing improved sensitivity compared to traditional photodetector-based methods. Our previous work focused on analyzing key parameters, such as sensitivity and spatial resolution, but did not consider practical aspects of selecting optimal modulation parameters. In this study, we develop a model based on Lang–Kobayashi rate equations for current-modulated optical feedback lasers and validate it through experimental investigations. Our findings reveal that optimal detection performance is achieved with a modulation depth of 0.048, a frequency sweeping range of 0.6 times the laser relaxation oscillation frequency, and a frequency sweeping step of 0.1 times the external cavity resonant frequency. [ABSTRACT FROM AUTHOR]

We report SmCoO3 nanofibers as an efficient catalyst for nitrate reduction to ammonia. This catalyst achieves a large NH3 yield of 14.4 mg h−1 mgcat.−1 and a high faradaic efficiency of 81.3% at −1.0 V vs. RHE in 0.1 M PBS with 0.1 M NaNO3, and it also displays excellent electrochemical durability and structural stability. Theoretical calculations indicate that Sm–O and Co–O bonds have an incredibly low adsorption energy of −0.1 eV, which can significantly reduce the applied potential and hence enhance the catalytic activity. [ABSTRACT FROM AUTHOR]